Effect of Kiwifruit on Gastrointestinal Fluid Distribution and Transit in Healthy Volunteers: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Effect of Kiwifruit on Gastrointestinal Fluid Distribution and Transit in Healthy Volunteers (NCT03303417), a randomized na study. The primary outcome is Relaxation Time in Ascending Colon.

2. Clinical Question

3. Trial Design

The study is registered as randomized, single-masked, and crossover, with an enrollment of 16 and a completed status. In a crossover design, a participant can receive both conditions at different times, allowing each person to contribute information under both conditions. That feature can reduce the influence of stable differences between people, but a valid paired interpretation depends on the sequence, timing, and analysis of the periods. The registry record does not report the treatment sequence, washout interval, or whether the posted comparisons account for within-participant pairing.

The interventions were kiwifruit and a calorie-matched sugar drink. The arm descriptions state that each was consumed twice a day for 3 days before MRI scanning. The brief summary describes twice-daily consumption for 2 days, then a study day with further kiwifruit or placebo, normal food, and repeated imaging. These descriptions differ on the pre-study duration; the registry record does not resolve that difference. The summary also says participants would complete a stool diary.

The primary measure was assessed over 0 - 8 hours. Secondary outcomes cover small bowel water content measured by MRI, colonic volume, colonic transit time, and bowel habit. The posted outcomes include continuous summaries for small bowel water content, colonic volume, and bowel habit; the registry record does not post a numerical comparison for colonic transit time. The record names MRI scanning as a diagnostic test and lists the University of Nottingham as sponsor. It does not report a phase beyond NA.

For a crossover trial, period effects, carryover, missing periods, and the correlation between a participant’s measurements under each condition can affect the analysis. The registry record does not report how these issues were handled. The arm summaries alone therefore do not establish whether the comparison estimates were derived using a paired crossover analysis.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

Reasons for not completing this period:

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

Population: 14 participants completed the study

6. Primary Endpoint

The registry lists the primary outcome as Relaxation Time in Ascending Colon, measured over 0 - 8 hours.

The primary endpoint is titled “Relaxation Time in Ascending Colon.” Its stated timeframe is 0 - 8 hours, and its description refers to the area under the curve of ascending-colon T1 measured on MRI, with measurements at 0, 1, 2, 3, 4, 5, 6, 7, and 8 hours post-intervention. The registry lists the unit as seconds*minutes, while the description says the T1 measurements are in milliseconds. This difference in labeling makes the exact unit of the area-under-the-curve summary unclear in the registry record.

An area under a time-course curve condenses measurements taken at multiple time points into a single summary of the level of the measure across the observation period. MRI provides a non-invasive way to image gut contents and features. In general, repeated imaging can characterize changes over time that a single measurement might miss. The trial’s stated purpose was to use gut imaging to assess changes associated with kiwifruit and improve understanding of its effects on gut contents.

The endpoint is reported as a mean with a standard deviation. The posted mean was 312.0 for kiwifruit and 256.0 for control, with a mean difference of 56.0. Because the scale labeling is internally unclear, these figures should be interpreted as the registry’s reported summaries rather than assigned a more specific physical interpretation than the record supports. The registry record does not report a clinical threshold for an important difference.

7. Results Posted in the Registry

• Kiwifruit: mean 312.00 versus 256.00 on control; difference 56.00 (95% CI -14.03 to 126.03), standardized effect d = 0.59; z-test p = 0.117.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Small Bowel Water Content Measured by MRI, in mL

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Kiwifruit: mean 85,530 versus 35,023 on control; difference 50,507 (95% CI 30,481 to 70,533), standardized effect d = 1.87; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Kiwifruit than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Colonic Volume

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Kiwifruit: mean 283,583 versus 243,182 on control; difference 40,401 (95% CI 826.20 to 79,976), standardized effect d = 0.76; z-test p = 0.045.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Kiwifruit than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Bowel Habit

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Kiwifruit: mean 1.46 versus 1.14 on control; difference 0.32 (95% CI -0.10 to 0.74), standardized effect d = 0.56; z-test p = 0.137.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Kiwifruit and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes show a mixed pattern rather than a single consistent level of evidence across measures. The small-bowel water-content and colonic-volume comparisons have positive mean differences with confidence intervals that exclude zero, whereas the bowel-habit interval includes zero. The registry lists colonic transit time among secondary outcomes but does not post a numerical comparison for it. The results therefore do not describe every listed secondary measure with the same completeness or degree of uncertainty.

These measures relate to the primary question by examining other aspects of gut contents, volume, transit, and bowel habit. Their direction can help describe whether different measured domains appear to move together, but they do not confirm the primary MRI endpoint. The primary result itself has a confidence interval that includes zero. The secondary pattern should thus be understood as complementary descriptive evidence, not as a replacement endpoint or a reason to disregard uncertainty in the primary comparison.

Unadjusted secondary results carry less weight because multiple outcomes create multiple opportunities for an apparently unusual comparison. Without a prespecified testing hierarchy or multiplicity adjustment, the registry’s p-values do not control the overall chance of false-positive findings across the outcome family. The record reports no multiplicity strategy and no analyses in its analysis listing. It is not possible to determine whether the posted secondary outcomes were planned as confirmatory, exploratory, or part of a particular decision sequence.

Also, endpoint definitions and timeframes differ. MRI-derived measures are summarized over 0 - 8 hours, while bowel habit is reported over 7 days. A pattern across these outcomes cannot be assumed to represent one shared biological process, and the registry does not report an analysis linking changes in one measure to changes in another. The overall secondary evidence is best read as a set of separate, limited comparisons that may inform further study rather than as a unified conclusion.

Secondary outcomes registered for this trial, for reference (only those above were recalculated):

• Small Bowel Water Content Measured by MRI, in mL
• Colonic Volume
• Colonic Transit Time
• Bowel Habit

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is a continuous measure reported as a mean and standard deviation. A mean describes the arithmetic average of the observations being summarized. A standard deviation describes how dispersed individual observations are around that average. It is not the same as the standard error, which describes the estimated sampling variability of a mean, nor is it a confidence interval for a treatment contrast.

What does the mean difference represent?

The posted primary comparison is a mean difference of 56.0, calculated in the registry’s comparison as the kiwifruit mean relative to the control mean. A difference expresses the contrast on the outcome’s own scale; it is not a percentage change. The registry gives a 95% confidence interval for this contrast, from -14.03 to 126.0. Because the interval includes zero, the data are compatible with no mean difference as well as with differences in either direction within the interval. This statement describes statistical uncertainty, not a probability assigned to a particular true effect.

The registry also reports an unadjusted p-value of 0.117 for the primary comparison. A p-value measures how unusual data at least as incompatible with a null hypothesis would be under a specified statistical model if the null hypothesis were true. It does not measure the size or importance of an effect. It also does not establish that the null is true when the value is not small. The record labels this p-value unadjusted and does not report whether a different primary analysis was conducted.

Why does the crossover design matter?

In a crossover study, the same participant may be observed under more than one condition. Measurements from the same person tend to be related, so a paired analysis can use the within-person contrast and account for that relationship. In general, a paired analysis can be more precise than treating the observations as unrelated when the within-person measurements are positively correlated. The amount of correlation and the exact analysis are needed to quantify that benefit. The registry record does not report those details, and the posted summaries do not include the participant-level paired differences. It is therefore not possible to confirm from the record whether the comparison reflects the crossover structure.

Period and carryover effects are also relevant in general. A period effect occurs when outcomes differ by study period for reasons other than the assigned condition. Carryover occurs when an earlier condition continues to influence an outcome in a later period. Sequence allocation and an adequate washout can be important design considerations, but the registry record does not report the sequence, washout, or any analysis of period or carryover effects. No assumptions about how these issues were addressed should be inferred from the crossover label alone.

How should the confidence interval be read?

A confidence interval gives a range of estimates compatible with the observed data under the method used to construct it. In repeated use of the same method under its assumptions, intervals would cover the true effect at the stated rate. For an individual trial, it is best read as a measure of uncertainty, rather than as a range that has a 95% probability of containing the true value. A wide interval indicates limited precision; whether it includes zero indicates whether a zero difference is among the values compatible with the analysis.

The primary interval extends from -14.03 to 126.0. This breadth matters as much as the point estimate: estimates ranging from a difference favoring control to a larger difference favoring kiwifruit remain compatible with the posted interval. The unit ambiguity in the registry record also constrains interpretation of the interval’s absolute scale.

What do the standard deviations and unadjusted comparisons add?

The primary standard deviations, 92.0 and 97.0, show that observations varied around their respective means. The mean difference and its confidence interval address the contrast, while the standard deviations describe spread within the conditions. Neither spread nor a standardized effect can resolve uncertainty about a missing crossover analysis or unclear outcome units.

The posted secondary comparisons are also unadjusted. This means the p-values are presented without a reported correction for testing multiple outcomes. When many outcomes are assessed, the chance of at least one apparently unusual result can increase even if none represents a real effect. That general concern is one reason secondary results are usually treated as supportive or exploratory unless a testing strategy is specified in advance. No multiplicity plan is reported in the registry record.

What can the planning illustrations tell readers?

The planning illustrations use the observed effect as a reference and show participant requirements for specified fractions of that effect. They are prospective calculations under listed assumptions, not evidence about the original trial’s design or a measure of the trial’s observed power. Their values depend on assumptions such as the chosen effect size, allocation, significance level, and statistical approximation. The record does not report the original sample-size justification or the assumptions used when the trial was designed. In a crossover trial, a planning calculation that does not reflect within-person correlation may not capture the design’s actual efficiency; the record does not specify whether the illustrations incorporate that correlation.

11. Confidence Intervals and Precision

The primary mean difference is 56.0, with a 95% confidence interval from -14.03 to 126.0. The interval is broad relative to the point estimate and includes zero. It also includes negative values, meaning that a difference in the opposite direction remains compatible with the posted analysis. The interval supports neither a precise estimate of the size of the contrast nor a confident direction for the primary outcome. The p-value of 0.117 is consistent with that uncertainty, but the confidence interval communicates more directly which effect values remain compatible with the analysis.

Confidence intervals should be interpreted in relation to both their width and the outcome scale. Here the primary unit is not clearly resolved: the endpoint is labeled in seconds*minutes, while its description refers to an area under the curve of T1 measured in milliseconds. The registry record does not report a threshold for a meaningful difference. Consequently, the numerical width cannot be translated into a judgment of clinical importance from the record alone.

General interpretation: a confidence interval is calculated using a statistical method and its assumptions. In repeated applications of that method, the stated confidence level describes the long-run coverage behavior. For a particular result, it does not mean there is a 95% probability that the true effect lies in the observed interval. It is a practical way to show the uncertainty around an estimate.

The crossover design raises an additional precision question. If measurements under the two conditions are paired, the within-participant correlation can affect the uncertainty of the contrast. The registry record does not report that correlation or whether the confidence interval accounts for pairing. The interval should therefore be read as the posted comparison, without assuming a particular crossover analysis.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are participants per arm for the continuous outcomes, not total events. The listed assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set to the stated fraction of the observed effect. These are planning assumptions for the displayed illustrations; the registry record does not report the original sample-size assumptions used to design the trial.

The 80% power column gives the participant requirement per arm for a planning scenario designed to have an 80% probability of detecting the specified effect under the calculation’s assumptions, if that effect were the true one. The 90% column uses a higher target probability under the same type of assumptions. Higher target power generally requires more participants. For instance, the primary-outcome illustration lists 45 participants per arm for planning for 100% of the observed effect at 80% power, and 60 for the corresponding 90% power scenario. For planning for 75% of the observed effect, it lists 80 participants per arm for 80% power and 107 for 90% power. For planning for 50% of the observed effect, the figures are 179 and 240 per arm, respectively.

Smaller effects are harder to distinguish from random variation, so the planning figures rise as the target effect becomes a smaller fraction of the observed effect. This is a general relationship, not a claim that the observed trial was designed around these values. The planning figures are not observed power. Observed power would not add useful information about the uncertainty already conveyed by the estimates and confidence intervals; the illustrations instead show how assumed effect size and target power affect prospective sample-size requirements.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = 56.000; pooled standard deviation σ = 94.533.
2. n = 2 × (1.96 + 0.842)² × 94.533² / 56.000² = 44.7, rounded up to 45 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
delta <- 56                      # observed difference in means
sigma <- 94.5330629991433                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(3303417)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 45 (80% power), 60 (90% power)
 75% of observed effect: n per arm = 80 (80% power), 107 (90% power)
 50% of observed effect: n per arm = 179 (80% power), 240 (90% power)
power.t.test: 45.7 
Simulated power at n = 45 per arm: 0.788 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists one primary endpoint and four secondary outcomes, but it does not report a statistical plan describing how the outcomes were prioritized for inference. It also does not report a multiplicity adjustment, a testing hierarchy, or a rule for interpreting secondary p-values. The posted secondary p-values are unadjusted. When several hypotheses are tested, the probability of at least one small p-value can increase; general methods such as family-wise error control or false-discovery-rate control address different forms of this problem. The registry record does not say that either approach was used.

The record reports no analyses in its analysis listing. It does post outcome summaries and comparisons, but it does not specify a statistical analysis plan, a primary model, or whether analyses were prespecified. It is therefore not possible to determine which analyses were confirmatory or whether any reported analysis differs from the planned approach.

Missing-data handling is not reported in the registry record. It does not say whether all randomized participants completed both conditions, whether any outcome measurements were missing, how missing measurements were handled, or whether imputation was used. The enrollment figure and the arm-level summary counts do not by themselves answer those questions, particularly in a crossover study where completion of each period can matter separately.

The analysis population is also not reported. The registry record does not specify whether the results use an intention-to-treat population, a per-protocol population, or another defined group. It does not describe exclusions after randomization. The displayed arm summaries give the number of observations reported for each condition, but they do not establish how those observations map to the randomized sequence or whether the same participants contributed under both conditions.

For a crossover design, a transparent analysis account would ordinarily clarify treatment sequence, period effects, carryover considerations, within-person correlation, and the handling of incomplete pairs. Those details are not reported in the registry record. Their absence limits assessment of both the uncertainty estimates and the scope of the conclusions; it does not establish that the investigators failed to address them in other study materials.

15. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 0% reporting threshold.

The serious adverse event figures report 0 affected participants among 14 at risk in the kiwifruit group and 0 among 14 at risk in the control group. The record also reports 0 affected by other adverse events in each group, with 14 at risk in each. Deaths are reported as 0 in both groups, and no serious adverse event terms are listed.

These figures describe the adverse events entered in the registry for the reported groups. A zero count means that no events of that category were recorded in the posted figures; it does not prove that an event is impossible or that there was no risk. With a limited number of observations, uncommon events may not be represented. The registry record does not provide further detail about how adverse events were solicited, defined, monitored, or attributed to an intervention, so the figures should not be interpreted as a comprehensive safety assessment.

16. What the Result Does, and Does Not, Mean

The posted primary result is an estimated mean difference of 56.0 for the ascending-colon MRI measure, with a 95% confidence interval from -14.03 to 126.0. This interval includes zero, and the unadjusted p-value is 0.117. The data therefore leave substantial uncertainty about the direction and size of the primary contrast. The finding is a description of this trial’s posted comparison, not a basis for saying that kiwifruit works or does not work.

The secondary outcomes add information about other measured domains, but they do not remove the uncertainty around the primary result. Some secondary comparisons have intervals excluding zero and some do not; the p-values are unadjusted, and the record does not report a multiplicity plan. The secondary evidence should not be treated as if it were a single confirmatory test or as proof of a broader effect across all gut measures.

The participants are described as healthy volunteers. Although constipation is listed among the condition tags and the summary discusses constipation as a general health problem, the record does not establish that the study enrolled people with constipation. It therefore does not directly answer a treatment question in a constipation-affected population. The registry record also does not report a clinical threshold linking the MRI measure to symptoms or a patient-important benefit.

The trial’s crossover design could permit within-person comparisons, but the registry does not report whether the posted analyses used paired data, how treatment periods were handled, or how missing observations were addressed. The endpoint unit is also unclear in the record. These are reasons to keep conclusions close to the posted numerical summaries rather than infer a precise physiological or clinical meaning.

Finally, the study concerns a short measurement period: the primary MRI timeframe is 0 - 8 hours, and bowel habit is reported over 7 days. The registry does not report longer-term follow-up. The results do not establish persistence, generalizability to other populations, or effects beyond the outcomes and timeframes recorded.

17. Why This Trial Matters Statistically

This trial illustrates why interpretation should start with the estimate and its uncertainty rather than a binary reading of a p-value. The primary point estimate is positive, but the confidence interval ranges across zero and a wide set of possible differences. Reporting the interval alongside the p-value makes clear that the central statistical issue is limited precision, not simply whether a threshold was crossed.

The crossover label also highlights the importance of matching an analysis to the design. In general, a crossover study can gain information from within-person comparisons, but that advantage depends on pairing and on appropriate handling of period and carryover effects. The registry gives the design label but not the analysis details needed to verify how those features were addressed. Statistical interpretation must therefore distinguish a registered design from a fully documented analysis.

The outcome record provides another useful lesson: endpoint definitions and units matter. The primary endpoint is described as an area under a time-course curve, but the listed unit and the description of the MRI measurements do not align clearly. Even a numerically precise estimate would be difficult to interpret if its scale is ambiguous. Clear measurement definitions are essential for comparing studies and relating results to meaningful changes.

Finally, the secondary findings demonstrate why multiple outcomes require a stated inferential strategy. Separate unadjusted results can be informative, but they should not be read as a set of independent confirmations. Together, the missing multiplicity and analysis details, the limited precision of the primary contrast, and the incomplete endpoint reporting show how registry summaries can support careful descriptive analysis while leaving key questions unresolved.

18. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

A central limitation is the mismatch between the primary endpoint’s listed unit, seconds*minutes, and the description of ascending-colon T1 measurements in milliseconds. The registry record does not clarify the intended unit for the area-under-the-curve endpoint, making it difficult to attach a physical interpretation to the estimate or compare its magnitude with other work.

The treatment-duration descriptions are also inconsistent. The brief summary describes twice-daily consumption for 2 days before a study day, while the arm descriptions state twice daily for 3 days before MRI scanning. The record does not resolve which description corresponds to the final protocol. This limits precise reconstruction of the exposure schedule from the registry alone.

Although the design is crossover, the registry record does not report sequence, washout, paired analysis, period effects, or carryover handling. It does not report the analysis population, missing-data approach, or participant flow across periods. These omissions make it difficult to assess whether the posted uncertainty reflects the design and how representative the analyzed observations are of the randomized experience.

The primary confidence interval is broad and includes zero. The registry does not report a minimally important difference for the MRI outcome, so statistical estimates cannot be mapped to a stated threshold of practical relevance. The record identifies healthy volunteers, limiting direct interpretation for people with constipation. It also does not post numerical results for the listed colonic transit-time outcome, and the secondary p-values are unadjusted. These limitations concern what can be concluded from the registry record; they do not show that additional study materials or analyses do not exist.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Effect of Kiwifruit on Gastrointestinal Fluid Distribution and Transit in Healthy Volunteers — NCT03303417.
• Registry record last updated 2019-06-17; status last verified 2019-03.
• Results first posted 2019-06-17.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

The registry record describes a completed randomized, single-masked crossover study sponsored by the University of Nottingham. Enrollment was 16, and the title identifies healthy volunteers. Participants received kiwifruit and a calorie-matched sugar drink in the crossover design; the intervention-duration descriptions differ between the brief summary and arm descriptions.

The primary outcome is ascending-colon relaxation time assessed by MRI over 0 - 8 hours. The posted mean difference was 56.0, with a 95% confidence interval from -14.03 to 126.0 and an unadjusted p-value of 0.117. The primary endpoint’s unit is unclear in the registry record. Secondary outcome summaries cover small bowel water content, colonic volume, and bowel habit, while no numerical comparison is posted for colonic transit time. The record lists no reported analyses and does not describe multiplicity, missing-data, or crossover-analysis methods.